Towards a Computational Model
of Dictyostelium discoideum

Jonathan Bachrach & Tom Hsu

Overview

Swarm robotics rely on a large number of robots with identical algorithms
to achieve global behaviors. This problem is analogous to biology in which
cells communicate with each other and work together to sustain life. Our
belief is that by constructing computational models of the behavior of
biological cells, we will 1) gain insights into connections between individual
and global behaviors, 2) begin to develop a computational theory for how
biology operates, and 3) start to understand how we might program biology
to accomplish tasks that we specify.

Problem Statement

Swarm robotics is becoming a reality as miniaturization and computerization
continue to lower the cost and increase the functionality of robots. Utilizing
a fleet of robots is becoming the main focus for many researchers. Researchers
are interested in creating algorithms and frameworks to allow robots to
work together efficiently. The study of how to use multiple robots effectively
to achieve common goals is called swarm robotics [1].

Swarm robotics can be seen as a problem already solved by nature to
sustain life for bacteria and multicellular organisms. Cells, analogous
to robots, work together to achieve global objectives. While individual
cells may perform different tasks than their neighbors, they share the
same blueprint - the genetic code. Swarm robotics strives to achieve the
same goal - to use a large number of robots with an identical algorithm
to solve problems collectively. We want to learn from biology to create
swarm robotic algorithms. A species of bacteria called Dictyostelium
discoideum is our particular source of inspiration and focus of inquiry.

Dictyostelium discoideum are soil amoebae capable of many different
techniques for survival. It is also known as the social amoebae or "cellular
slime molds". These amoebae can form multicellular organisms in order
to increase their chances for survival and reproduction. The mechanisms
of such social behaviors are useful building blocks for distributed robotic
control. In other words, knowledge can be gleaned from Dictyostelium
bacteria to teach a swarm of robots to work together.

The goal of this project is to model the life of Dictyostelium discoideum.
Programming the behaviors of the bacteria as swarm robots will grant insights
on the connections between individual behaviors and global behaviors.
The algorithms will be constructed to be reusable and composable. We will
use the Proto programming language [5], a distributed stream processing
language for sensor/actuator networks.

Related Work

McLurkin [1] has done pioneering work in swarm robotics. In particular,
he has developed a C library of group behaviors inspired by ant colonies
and deployed them on 128 small mobile robots. In contrast, this research
aims to explain the Dictyostelium discoideum development cycle
using a computational model built on top of a high level programming language.
This computation model will allow us to better understand how nature has
tackled the problem of programming a swarm of identical robots.

The behaviors of Dictyostelium discoideum have been intensely
studied by biologists. The initial stages of development are well understood.
The mechanism for the aggregation into a loose mound is explained well
by Scott Camazine in his Self-Organization in Biological Systems [2].
Dictyostelium generates chemical waves through refractory period and digestion
and release of the cAMP chemicals. The wave and aggregation model have
been previously tested in simulation [4]. The simulation mirrors the experimental
observations in laboratories. We will expand this work to include the
whole development cycle of Dictyostelium and to do so out of composable
and reusuable parts.

Proposed Work

The goal of the project is to describe all the developmental stages
for Dictyostelium discoideum. Our project involves two major steps:

Step 1: Simulation environment. While the basic Proto language is fairly
mature, its support for biological modeling is only preliminary. More
low level building blocks need to be present in order to effective describe
Dictyostelium bacteria. One of the major questions is how to express
chemical diffusion in an abstract and composable manner. Other basic mechanisms
include refractory periods, gradient sensing, chemotaxis, etc. The simulation
will also need a graphical display to show the actual movements of the
simulated bacteria. A graphical display will be invaluable in debugging
and demonstrating the developmental algorithms quickly.

Step 2: Module library. The main purpose of this project will be to
develop a library of composable modules that enable robots to work together
efficiently. With the abstraction mechanisms provided by the Proto language,
we will write each of the developmental algorithms in a concise and natural
fashion. Basic movements include how to collect the bacteria together
and differentiate them to have a head and a tail, etc.

Progress

To date, we have augmented the Proto language and runtime to include
support for chemical channels and communication. Using this substrate,
we have simulated the wave propagation and cell aggregation mechanisms.
Finally, we have developed preliminary models for multicellular differentiation
in the aggregated amoebae.